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Industrial Processing of Complex Fluids:Formulation and Modeling
J. C. Scovel, CIC-3
S.Bleasdale,
CIC-3G. M. Forest, Eng. Mech. Dept., Ohio StateU.
S. Bechtel, Eng. Mech. Dept., Ohio State U.
DOE Office of Scientific and Technican Information (OSTI)
DISCLAIMER
This report was prepared as an a m u n t of work sponsored by an agency of the United Stacts
Government. Neithe r the United Sta tes Government nor any agency thereof, nor any of their
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Industrial Processing of Complex Fluids: Formulation andModel ing
James C. Scovel*and S hirley BleasddleComputing, Information, and Comm unications D ivision, Los Alamos National Laboratory
Greg M. Forest and Steve BechtelEngineering Mechanics Department, Ohio State University
AbstractThis is the final report of a three-year, Laboratory Directed Research andDevelopment (LDR D) project at the Los Alamos National Laboratory (LANL).The production of many important commercial materials involves the evolutionof a complex fluid through a cooling phase into a hardened prod uct. Textilefibers, high-strength fibers such as KEVLAR and VECTRAN, plastics,chopped-fiber compounds, and fiber optical cable are but a few examples of
suc h materials. Industry contacts for each of these m aterials are keenly awareof the physics and chemistry that dominate their manufacturing processes anddesire to replace experiments with on-line, real time m odels of these processes.Industry scientists are equally aware of a hum bling fact: solu tions to theirproblems are not jus t a matter of technology transfer, but require a fundamentaldescription and simulation of their processes that lies just beyond the currentstate of science. Th e goals of our project are to develop models that can be usedto optimize macroscopic properties of the solid product, to identify sources ofundesirable defects, and to seek boundary-temperature and flow-and-materidcontrols to optimize desired properties.
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Background and Research Objectives
Th e important elemen ts of these material processes consist of a com plex fluid, usually
with s ignificant non-Ne wtonian rheology, temperature d ependen t viscosity, thermal variations
from liquid to solid phase, and the m ost elusive and least understood orientation effects at
particular length scales (molecular scales in KEVLAR type materials, intermediate or
meso scales in many textile fibers and plastics, and macro scales in chopped -fiber comp ounds)
which cou ple to the thermal flow and solidification process. Internal length-scale orientation of
the finished produc t dominates the desired properties, and yet this is the weake st link from the
basic science perspective. W e note the common ality of this multiple length-scale coupling to
various materials processing problems addressed by others at Los Alamos.As a result of the complexities of these systems, significant compromises are made to
achieve the existing crud e models which fall short of their full potential-to troubleshoot
existing processes and materials, and to perfoim parameter stud ies for the design of new
* Principal Investigator, E-mail: jcs@'lanl.gov
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materials and processes. For example, the Hoechst-Celanese Corporation uses a fiber spinning
mod el which ignores polymer orientation in the flow and then ap plies empirical relations to
infer orientation from the computed stress field. Th is orientation inform ation is then used to
predict tensile strength and optical properties of the fiber. Th is is only one of the many features
absent: transient dynamics and stability infoimation, significant gradients transverse to the
fiber axis in temperature are presumed zero, etc.
Clearly, a coupled thermal-flow-orientation-solidification mod el of this free surface
flow (and related problems) is both unavailable and highly desirable. Th e goal of this project is
to develop th e capability to predict, for examp le, the orientatio dstres s field relationship as a
function of model parameters. Such high-level models can be used to optimize macroscopic
properties of the solid product, to identify sources of undesirable defects, and to seek
bound ary, temp erature, flow and material contro ls to optimize desired properties.
Importance to LANL’s Science and Technology Base and National R& D Needs
Th e coupling of various length-scale orientation effects to flows is itself a critical basic
scientific problem. Th e added effects of temperature dependence and phase change to
solidification, with free surfaces, pose an opportunity to advance fundamental science and
simultaneously assist US industry in gaining a com petitive advantage.
basic material science efforts here at LAN L concernin g the processing of m etals and ceramics.
Although the specific physics and engineering of metals and ceramics ar e different, at the
fundam ental level they are remarkably similar: internal length-scale structures (orientation
Furtherm ore, these capabilities m ay contribu te to and gain from other industrial and
effects) couple to the macroscopic length sc ales and critically determine the desired
macroscopic properties such as strength, defects, and post-processing deformation.
R ic hard k S a r (CMS), they must m odel the melting, flow , deformation and re-solidification of
the metal, which is fundamentally influenced by the microstructure. Th e technical and
technological impact of accurate, flexible processing co des could b e dramatic. As textile and
optical cable industry con tacts have noted, a 5-1096 gain in product efficiency translates to
market domination. Demo nstration of such capabilities should encou rage industry to engage in
CRADAs to collaborate towards the develo pmen t of on-line codes to aid in the industrial
production of these advanced m aterials.
For exam ple, in the laser welding project at Los Alamos of Tony Rollet (MST-6) and
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Scientific Approach and Accomplishments
Initially, we began by concentrating on the mold filling and solidification process. In
particular a highly viscous me lt is forced into a mold and simultaneously cooled to o btain a
solid with prescribed shape. M odeling this process amounts to unders tanding how to model
and simulate solidification in the presence of slow flow in a prescribed doma in. W e have
isolated th e areas that must be understood individually and then coupled.
1. Flow of the molten polymer.
2. Heat trm sfer in the melt domain.
3. Interface mechanics.
4. Solidification of the melt.
5. He at transfer in the solid domain.
6. Thermomechanical stress and defoimation analysis of the solid.
Each of the abo ve areas will constitute a module in a driver code.
W e have searched for a finite element fluid code that can handle phase chang es and non-
Newtonian fluids. W e have found that th e code FIDAP appears to suit our needs.
W e have successfully implemented the fluid code FIDAP in two-dimensional geometry on
a quasi-steady state solidification problem in sim ple geometry.
W e began deriving equ ations coupling the orientation effects based on Erickse n's liquid
crystal models. The se equations can be simplified to standard form and at the sam e time
give qualitative theoretical characterizations of o bserved physical ph enomena.
W e derived a multiscale foimulation of complex f-luidsbased on a nonlinear state space
model w here the observation equation corresponds to the relation between the sm all scales and
the larger scale structures. Significant information is available regarding the so lutions of such
mod els for linear systems through application of the Kalman filter. Consequently, we reduced
the scope to linear systems. How ever, even then our researches show ed that little is known
about multiscale state space models. Consequently, we concentrated on the relevant elementary
unsolved problem: how to disaggregate linear time series data.
W e developed and tested a disaggregation procedure for time series data based on an
EM (expectation and m aximization) type algorithm we derived. How ever, testing this
algorithm on ARMA (auto regressive moving average) time series mod els gave m ixed results
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until we discovered the work of Al-O sh who described the likelihood function fo r the method
[13. Ou r techniques combined with maximizing th e likelihood function gav e very interesting
results as follows:
The parameters of the ARM A mo dels generating the original data can be well determined.
The actual data is not particularly well determined by this method w hen com pared to a naive
disaggreg ation technique at a pointwise level. How ever, upon compu ting autocorrelation
functions, it is observed that our technique produces d ata that is more like data from a
stochastic process of the corre ct type.
W e produced a n extensive investigation into the behavior of our algorithm in the specific
parameter regimes of AR, M A, and ARMA time series models with interesting results.
Th e relevance of these results to complex fluids is that if the pointwise stationary data is all
that is impo rtant, more naive approaches for multiscale descriptions mig ht be relevant.
However, since the relaxational modes of a complex fluid are related to how the fluid is
evolving and how th e different scales are interacting, such a technique sh ow s promise.
The next step in such an evaluation is the development of a nonlinear analogu e of th e
Kalman filter.
Publica tion
1. Bleasdale, S., Bun-,T., and J. Scovel, “Disaggregating Tim e Series Data,” Los Alamos
Nationa l Laboratory report, in preparation.
Reference
[11 Al-Osh, M ., “A Dynam ic Linear Model Approach for Disaggregating T ime SeriesData,”
Journal of Forecasting, 8 (2), 85-96 (1989).
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